Model-J SupViT
Collection
998 items
โข
Updated
This model is part of the Model-J dataset, introduced in:
Learning on Model Weights using Tree Experts (CVPR 2025) by Eliahu Horwitz*, Bar Cavia*, Jonathan Kahana*, Yedid Hoshen
๐ Project | ๐ Paper | ๐ป GitHub | ๐ค Dataset
| Attribute | Value |
|---|---|
| Subset | SupViT |
| Split | train |
| Base Model | google/vit-base-patch16-224 |
| Dataset | CIFAR100 (50 classes) |
| Parameter | Value |
|---|---|
| Learning Rate | 0.0003 |
| LR Scheduler | linear |
| Epochs | 3 |
| Max Train Steps | 999 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 124 |
| Random Crop | False |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9979 |
| Val Accuracy | 0.9325 |
| Test Accuracy | 0.9324 |
The model was fine-tuned on the following 50 CIFAR100 classes:
pine_tree, trout, bus, clock, plate, bottle, shrew, road, tulip, keyboard, pear, palm_tree, spider, tractor, wardrobe, chair, oak_tree, bowl, lobster, boy, ray, hamster, caterpillar, sea, aquarium_fish, castle, bicycle, dinosaur, kangaroo, willow_tree, butterfly, crocodile, cup, camel, pickup_truck, bed, mouse, sunflower, motorcycle, apple, bear, porcupine, squirrel, beaver, lizard, otter, crab, snake, seal, train
Base model
google/vit-base-patch16-224